Unit of Nephrology, General Hospital, Piazzale Ospedale, 23, 31100, Treviso, Italy.
Department of Medicine, University of Perugia, Perugia, Italy.
J Nephrol. 2021 Apr;34(2):325-335. doi: 10.1007/s40620-020-00946-3. Epub 2021 Jan 2.
Over 80% (365/454) of the nation's centers participated in the Italian Society of Nephrology COVID-19 Survey. Out of 60,441 surveyed patients, 1368 were infected as of April 23rd, 2020. However, center-specific proportions showed substantial heterogeneity. We therefore undertook new analyses to identify explanatory factors, contextual effects, and decision rules for infection containment.
We investigated fixed factors and contextual effects by multilevel modeling. Classification and Regression Tree (CART) analysis was used to develop decision rules.
Increased positivity among hemodialysis patients was predicted by center location [incidence rate ratio (IRR) 1.34, 95% confidence interval (CI) 1.20-1.51], positive healthcare workers (IRR 1.09, 95% CI 1.02-1.17), test-all policy (IRR 5.94, 95% CI 3.36-10.45), and infected proportion in the general population (IRR 1.002, 95% CI 1.001-1.003) (all p < 0.01). Conversely, lockdown duration exerted a protective effect (IRR 0.95, 95% CI 0.94-0.98) (p < 0.01). The province-contextual effects accounted for 10% of the total variability. Predictive factors for peritoneal dialysis and transplant cases were center location and infected proportion in the general population. Using recursive partitioning, we identified decision thresholds at general population incidence ≥ 229 per 100,000 and at ≥ 3 positive healthcare workers.
Beyond fixed risk factors, shared with the general population, the increased and heterogeneous proportion of positive patients is related to the center's testing policy, the number of positive patients and healthcare workers, and to contextual effects at the province level. Nephrology centers may adopt simple decision rules to strengthen containment measures timely.
超过 80%(365/454)的全国中心参与了意大利肾脏病学会 COVID-19 调查。截至 2020 年 4 月 23 日,在接受调查的 60441 名患者中,有 1368 人感染。然而,各中心的比例存在显著异质性。因此,我们进行了新的分析,以确定感染控制的解释因素、背景影响和决策规则。
我们通过多水平模型研究了固定因素和背景影响。分类回归树(CART)分析用于制定决策规则。
血液透析患者的阳性率增加与中心位置有关[发病率比(IRR)1.34,95%置信区间(CI)1.20-1.51]、阳性医护人员(IRR 1.09,95%CI 1.02-1.17)、全员检测政策(IRR 5.94,95%CI 3.36-10.45)和普通人群中的感染比例(IRR 1.002,95%CI 1.001-1.003)(均 P<0.01)。相反,封锁持续时间具有保护作用(IRR 0.95,95%CI 0.94-0.98)(P<0.01)。省级背景影响占总变异性的 10%。腹膜透析和移植病例的预测因素是中心位置和普通人群中的感染比例。通过递归分区,我们确定了普通人群发病率≥229/100,000 和≥3 名阳性医护人员的决策阈值。
除了与普通人群共同的固定危险因素外,阳性患者比例的增加和异质性与中心的检测政策、阳性患者和医护人员数量以及省级背景影响有关。肾脏病中心可以采用简单的决策规则,及时加强控制措施。